I guess Einsum is much cleaner, but I already had started with this and
maybe someone likes it, this is fully vectorized and uses a bit of funny
stuff too:
# The dot product(s), written using broadcasting rules:
a = -(x.reshape(-1,1,3) * x[...,None])
# Magic, to avoid the eye thing, takes all
Hello,
On Tue, 2012-03-06 at 13:00 +0100, Jose Miguel Ibáñez wrote:
Hello everyone,
does anyone know of an efficient implementation (maybe using
numpy.where statement) of the next code for data cube (3d array)
combining ?
You use the axis keyword/argument to sum, at which point you want
://mail.scipy.org/mailman/listinfo/numpy-discussion
From eed2abca6144e16c5d9ca208ef90dd01f7dd6009 Mon Sep 17 00:00:00 2001
From: Sebastian Berg sebast...@sipsolutions.net
Date: Thu, 9 Aug 2012 17:17:32 +0200
Subject: [PATCH] Fix reshaping of arrays with stride 0 in a dimension with
size of more then 1
Hello,
Just to throw it in, if you do not mind useing scipy, you can use its
multidimensional correlate method instead:
stamp = np.ones((3,3,3))
stamp[1,1,1] = 0
num_neighbours = scipy.ndimage.correlate(x, stamp, mode='wrap'))
In the link np.roll is used to implement periodic boundaries
Hey,
Inspired by an existing PR into numpy, I created two functions based on
stride_tricks which I thought might be useful inside numpy. So if I get
any feedback/pointers, I would add some tests and create a PR.
The first function rolling_window is to create for every point of the
original
Hello,
On Mo, 2012-08-20 at 20:55 +1000, Andrew Nelson wrote:
Dear list,
I observe a difference when I try to load a 2D numpy array from a file
object compared to if I supply a filename viz:
np.version.version
'1.5.1'
f=open('fit_theoretical.txt')
a=np.loadtxt(f)
a.shape
(1000,)
Hey,
No idea if this is simply not support or just a bug, though I am
guessing that such usage simply is not planned. However, this also has
to do with buffering, so unless the behaviour is substantially changed,
I would not expect even predictable results. I have used things like
a[1:] += a[:-1]
On Tue, 2012-09-18 at 08:42 -1000, Eric Firing wrote:
On 2012/09/18 7:40 AM, Benjamin Root wrote:
On Fri, Sep 7, 2012 at 12:05 PM, Nathaniel Smith n...@pobox.com
mailto:n...@pobox.com wrote:
On 7 Sep 2012 14:38, Benjamin Root ben.r...@ou.edu
mailto:ben.r...@ou.edu wrote:
Hey,
I have written a small PR, to fix np.delete, since it would change the
behavior a little (to the better IMO) I think I should also write to the
list? So here is the problem with np.delete:
1. When using slices with negative strides, it does not work (best case)
or give even wrong results.
Hey,
this is indirectly related (I think it might fix many of these memmap
oddities though?)...
Why does the memmap object not implement:
def __array_wrap__(self, obj):
if self is obj:
return obj
return np.array(obj, copy=False, subok=False)
By doing so if we
Hey,
Numpy currently assumes that if ndim 1 then it is impossible for any
array to be both C- and F-contiguous, however an axes of dimension 1
does have no effect on the memory layout. I think I have made most
important changes (actually really very few), though I bet some parts of
numpy still
Hi,
I have a bit of trouble figuring this out. I would have expected
np.asarray(array) to go through ctors, PyArray_NewFromArray, but it
seems to me it does not, so which execution path is exactly taken here?
The reason I am asking is that I want to figure out this behavior/bug,
and I really am
(on a mobile)
512-826-7480
On Sep 22, 2012, at 1:01 PM, Sebastian Berg sebast...@sipsolutions.net
wrote:
Hi,
I have a bit of trouble figuring this out. I would have expected
np.asarray(array) to go through ctors, PyArray_NewFromArray, but it
seems to me it does not, so which
On Sat, 2012-09-22 at 13:12 -0500, Travis Oliphant wrote:
Check to see if this expression is true
no is o
In the first case no and o are the same object
Travis
--
Travis Oliphant
(on a mobile)
512-826-7480
On Sep 22, 2012, at 1:01 PM, Sebastian Berg sebast
On Sun, 2012-09-23 at 18:54 +0100, Nathaniel Smith wrote:
On Sat, Sep 22, 2012 at 10:24 PM, Sebastian Berg
sebast...@sipsolutions.net wrote:
In case you are interested, the second (real odditiy), is caused by
ISFORTRAN and IS_F_CONTIGUOUS mixup, I have found three occurances where
I think
Hey,
About the imaginary part being ignored for all/any function...
snip
The all method fails also.
In [1]: a = zeros(5, complex)
In [2]: a.imag = 1
In [3]: a.all()
Out[3]: False
Chuck
I believe this diff fixes the issue (also posted on Tracker), I doubt
its the best way to fix
On Mon, 2012-10-01 at 10:59 -0600, Charles R Harris wrote:
On Mon, Oct 1, 2012 at 10:09 AM, Sebastian Berg
sebast...@sipsolutions.net wrote:
Hey,
About the imaginary part being ignored for all/any function...
snip
On Wed, 2012-10-10 at 12:55 -0400, Cera, Tim wrote:
On Wed, Oct 10, 2012 at 1:58 AM, Travis E.
Oliphant notificati...@github.com wrote:
I'm not sure what to make of no comments on this PR. This
seems like a useful addition. @timcera are you still
interested in having
On Thu, 2012-10-25 at 17:48 -0400, David Warde-Farley wrote:
I submitted a pull request and one of the Travis builds is failing:
https://travis-ci.org/#!/numpy/numpy/jobs/2933551
Don't worry about that failure on Travis... It happens randomly on at
the moment and its unrelated to
Hey
On Thu, 2012-10-25 at 19:27 -0600, Charles R Harris wrote:
Hi Sebastian,
snip
You seem to becoming more involved in the code maintenance. Would you
be interested in gaining commit rights at some point?
Maybe, but honestly I am not sure if I will keep following numpy very
closely in
Hey,
On Mon, 2012-10-29 at 09:54 -0400, Benjamin Root wrote:
This error started showing up in the test suite for mpl when using
numpy master.
AttributeError: incompatible shape for a non-contiguous array
The tracebacks all point back to various code points where we are
trying to set the
the problem to this
commit:
https://github.com/numpy/numpy/commit/c48156dfdc408f0a1e59ef54ac490cccbd6b8d73
Patrick.Marsh@buxton numpy git bisect good
c48156dfdc408f0a1e59ef54ac490cccbd6b8d73 is the first bad commit
commit c48156dfdc408f0a1e59ef54ac490cccbd6b8d73
Author: Sebastian Berg
Hey,
On Wed, 2012-10-31 at 20:22 -0400, David Warde-Farley wrote:
On Wed, Oct 31, 2012 at 7:23 PM, Moroney, Catherine M (388D)
catherine.m.moro...@jpl.nasa.gov wrote:
Hello Everybody,
I have the following problem that I would be interested in finding an
easy/elegant solution to.
I've
On Thu, 2012-11-01 at 01:30 +0100, Sebastian Berg wrote:
Hey,
On Wed, 2012-10-31 at 20:22 -0400, David Warde-Farley wrote:
On Wed, Oct 31, 2012 at 7:23 PM, Moroney, Catherine M (388D)
catherine.m.moro...@jpl.nasa.gov wrote:
Hello Everybody,
I have the following problem that I
Hey,
On Thu, 2012-11-08 at 14:44 -0800, Nicolas SCHEFFER wrote:
Well, hinted by what Fabien said, I looked at the C level dot function.
Quite verbose!
But starting line 757, we can see that it shouldn't be too much work
to fix that bug (well there is even a comment there that states just
On Fri, 2012-11-09 at 00:24 +0100, Sebastian Berg wrote:
Hey,
On Thu, 2012-11-08 at 14:44 -0800, Nicolas SCHEFFER wrote:
Well, hinted by what Fabien said, I looked at the C level dot function.
Quite verbose!
But starting line 757, we can see that it shouldn't be too much work
to fix
On Fri, 2012-11-09 at 14:52 -0800, Nicolas SCHEFFER wrote:
Ok: comparing apples to apples. I'm clueless on my observations and
would need input from you guys.
Using ATLAS 3.10, numpy with and without my changes, I'm getting these
timings and comparisons.
#
#I. Generate matrices using
Hey,
On Mon, 2012-11-12 at 08:48 -0500, Alan G Isaac wrote:
On 11/9/2012 12:21 PM, Nathaniel Smith wrote:
you might want to double-check that the
np.random.choice in 1.7 actually*does* give an error if the input
array is not 1-d
Any idea where I can look at the code?
I browsed
On Mon, 2012-11-12 at 17:52 +0100, Nathaniel Smith wrote:
On Mon, Nov 12, 2012 at 5:31 PM, Alan G Isaac alan.is...@gmail.com wrote:
In a comment on the issue https://github.com/numpy/numpy/issues/2724
Sebastian notes:
it could also be reasonable to have size=None as default and have it
On Mon, 2012-11-12 at 18:36 -0500, Alan G Isaac wrote:
On 11/12/2012 5:46 PM, Nathaniel Smith wrote:
Want to make a pull request?
Well, I'd be happy to help Sebastien to change the
code, but I'm not a git user.
I have created a pull request, but tests are still needed... If you like
it
On Mon, 2012-11-12 at 22:44 -0500, Alan G Isaac wrote:
On 11/12/2012 8:18 PM, Sebastian Berg wrote:
I have created a pull request
This is still a bit different than I thought you intended.
With `size=None` we don't get an element,
but rather a 0d array.
You are right, it should
Hey,
On Wed, 2012-11-21 at 01:12 -0800, Terry J. Ligocki wrote:
I am having a problem with reshape crashing:
python
Python 2.6.4 (r264:75706, Jan 16 2010, 21:11:47)
[GCC 4.3.2] on linux2
Type help, copyright, credits or license for more
information.
On Wed, 2012-11-21 at 22:58 -0500, josef.p...@gmail.com wrote:
On Wed, Nov 21, 2012 at 10:35 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Wed, Nov 21, 2012 at 7:45 PM, josef.p...@gmail.com wrote:
On Wed, Nov 21, 2012 at 9:22 PM, Olivier Delalleau sh...@keba.be wrote:
On Thu, 2012-11-22 at 16:05 +0100, Daπid wrote:
On Thu, Nov 22, 2012 at 3:54 PM, josef.p...@gmail.com wrote:
Why don't operations on empty arrays not return empty arrays?
Because functions like mean or std are expected to return a scalar.
Functions that are piecewiese can (and should)
On Fri, 2012-11-23 at 10:49 +, Nathaniel Smith wrote:
On 23 Nov 2012 03:34, Charles R Harris charlesr.har...@gmail.com
wrote:
Examples,
In [13]: ones(()).flags.writeable
Out[13]: True
In [14]: (-ones(())).flags.writeable
Out[14]: False
In [15]:
On Mon, 2012-11-26 at 13:54 -0500, Skipper Seabold wrote:
I discovered this because scipy.optimize.fmin_powell appears to
squeeze 1d argmin to 0d unlike the other optimizers, but that's a
different story.
I would expect the 0d array to behave like the 1d array not the 2d as
it does below.
On Wed, 2012-11-28 at 11:11 -0500, Skipper Seabold wrote:
On Tue, Nov 27, 2012 at 11:16 AM, Sebastian Berg
sebast...@sipsolutions.net wrote:
On Mon, 2012-11-26 at 13:54 -0500, Skipper Seabold wrote:
I discovered this because scipy.optimize.fmin_powell appears
Hey,
Maybe someone has an opinion about this (since in fact it is new
behavior, so it is undefined). `np.take` used to not allow 0-d/scalar
input but did allow any other dimensions for the indices. Thinking about
changing this, meaning that:
np.take(np.arange(5), 0)
works. I was wondering if
Hi,
maybe someone has an opinion about how this can be handled and was not
yet aware of this.
In current numpy master (probably being reverted), the definition for
contiguous arrays is changed such that it means Contiguous in memory
and nothing more. What this means is this:
1. An array of size
On Wed, 2012-12-12 at 20:48 +, Nathaniel Smith wrote:
On Wed, Dec 12, 2012 at 8:20 PM, Ralf Gommers ralf.gomm...@gmail.com wrote:
On Tue, Dec 11, 2012 at 5:44 PM, Neal Becker ndbeck...@gmail.com wrote:
I think it's a misfeature that a floating point is silently accepted as an
index.
Hey,
this is probably just because I do not have any experience with bisect
and the like, but when I try running a bisect keep running into:
ImportError:
/home/sebastian/.../lib/python2.7/site-packages/numpy/core/multiarray.so:
undefined symbol: PyDataMem_NEW
or:
RuntimeError: module compiled
On Sat, 2013-01-05 at 00:17 +0100, Sebastian Berg wrote:
Hey,
this is probably just because I do not have any experience with bisect
and the like, but when I try running a bisect keep running into:
Nevermind that. Probably I just stumbled on some bad versions...
ImportError:
/home
On Sun, 2013-01-06 at 08:58 +0100, Dag Sverre Seljebotn wrote:
On 01/05/2013 10:31 PM, Nathaniel Smith wrote:
On 5 Jan 2013 12:16, Matthew Brett matthew.br...@gmail.com wrote:
Hi,
Following on from Nathaniel's explorations of the scalar - array
casting rules, some resources on rank-0
Question for everyone, is this really reasonable:
import numpy as np
from operator import index
index(np.array([[5]]))
5
int(np.array([[5]]))
5
[0,1,2,3][np.array([[2]])]
2
To me, this does not make sense, why should we allow to use a high
dimensional object like a normal scalar (its ok for
On Sun, 2013-01-06 at 13:28 -0500, josef.p...@gmail.com wrote:
On Sun, Jan 6, 2013 at 12:57 PM, Sebastian Berg
sebast...@sipsolutions.net wrote:
Question for everyone, is this really reasonable:
import numpy as np
from operator import index
index(np.array([[5]]))
5
int(np.array([[5
On Tue, 2013-01-08 at 19:59 +, Nathaniel Smith wrote:
On 8 Jan 2013 17:24, Andrew Collette andrew.colle...@gmail.com wrote:
Hi,
I think you are voting strongly for the current casting rules, because
they make it less obvious to the user that scalars are different from
arrays.
On Thu, 2013-01-10 at 11:32 +0100, Mads Ipsen wrote:
Hi,
I find this to be a little strange:
x = numpy.arange(10)
isinstance(x[0],int)
gives True
y = numpy.where(x 5)[0]
isinstance(y[0],int)
gives False
isinstance(y[0],long)
Check what
On Thu, 2013-01-10 at 11:32 +0100, Mads Ipsen wrote:
Hi,
I find this to be a little strange:
x = numpy.arange(10)
isinstance(x[0],int)
gives True
y = numpy.where(x 5)[0]
isinstance(y[0],int)
gives False
isinstance(y[0],long)
Check what
On Sat, 2013-01-12 at 00:26 +0100, Chao YUE wrote:
Hi,
I don't know how others think about this. Like you point out, one can
use
np.nonzero(a==np.max(a)) as a workaround.
For the second point, in case I have an array:
a = np.arange(24.).reshape(2,3,4)
suppose I want to find the
Hey,
On Tue, 2013-01-22 at 10:21 +0100, Todd wrote:
I am trying to create a subclass of ndarray that has additional
attributes. These attributes are maintained with most numpy functions
if __array_finalize__ is used.
You can cover a bit more if you also implement `__array_wrap__`, though
On Tue, 2013-01-22 at 13:44 +0100, Sebastian Berg wrote:
Hey,
On Tue, 2013-01-22 at 10:21 +0100, Todd wrote:
I am trying to create a subclass of ndarray that has additional
attributes. These attributes are maintained with most numpy functions
if __array_finalize__ is used.
You can
On Tue, 2013-01-29 at 14:53 +0100, Lluís wrote:
Gregor Thalhammer writes:
Am 28.1.2013 um 23:15 schrieb Lluís:
Hi,
I have a somewhat convoluted N-dimensional array that contains information
of a
set of experiments.
The last dimension has as many entries as iterations in the
On Wed, 2013-01-30 at 10:24 +0100, Todd wrote:
On Tue, Jan 22, 2013 at 1:44 PM, Sebastian Berg
sebast...@sipsolutions.net wrote:
Hey,
On Tue, 2013-01-22 at 10:21 +0100, Todd wrote:
The main exception I have found is concatenate
On Wed, 2013-02-06 at 10:18 +0100, Dag Sverre Seljebotn wrote:
On 02/06/2013 08:41 AM, Charles R Harris wrote:
On Tue, Feb 5, 2013 at 11:50 PM, Jason Grout
jason-s...@creativetrax.com mailto:jason-s...@creativetrax.com wrote:
On 2/6/13 12:46 AM, Charles R Harris wrote:
if
On Wed, 2013-02-06 at 13:31 +, gk230-free...@yahoo.de wrote:
Hi,
I'm currently trying to build numpy 1.6.2 for python python 3.3 from ports on
FreeBSD. Unfortunately, the setup.py execution fails because some [1] gcc
command trying to access _numpyconfig.h fails since _numpyconfig.h is
On Wed, 2013-02-06 at 13:08 -0500, josef.p...@gmail.com wrote:
I'm convinced that I saw a while ago a function that uses a list of
interval boundaries to index into an array, either to iterate or to
take.
I thought that's very useful, but didn't make a note.
Now, I have no idea where I saw
Hey,
On Sun, 2013-02-17 at 11:50 +0100, Andreas Hilboll wrote:
In my numpy 1.6.1 (from Ubuntu 12.04LTS repository), the docstring of
np.percentile is wrong. I'm not just submitting a PR because I don't
understand something.
in the Notes and Examples sections, there seems to be some
On Tue, 2013-02-19 at 10:00 -0500, Tony Ladd wrote:
I want to accumulate elements of a vector (x) to an array (f) based on
an index list (ind).
For example:
x=[1,2,3,4,5,6]
ind=[1,3,9,3,4,1]
f=np.zeros(10)
What I want would be produced by the loop
for i=range(6):
Hello all,
currently the `__contains__` method or the `in` operator on arrays, does
not return what the user would expect when in the operation `a in b` the
`a` is not a single element (see In [3]-[4] below).
The first solution coming to mind might be checking `all()` for all
dimensions given in
On Mon, 2013-02-25 at 16:33 +, Nathaniel Smith wrote:
On Mon, Feb 25, 2013 at 3:10 PM, Sebastian Berg
sebast...@sipsolutions.net wrote:
Hello all,
currently the `__contains__` method or the `in` operator on arrays, does
not return what the user would expect when in the operation
on the other hand it would only do something reasonable when otherwise
an error would be thrown and it definitely is useful and compatible to
what anyone else might expect.
On Feb 25, 2013 5:34 PM, Nathaniel Smith n...@pobox.com wrote:
On Mon, Feb 25, 2013 at 3:10 PM, Sebastian Berg
On Mon, 2013-02-25 at 10:50 -0500, Skipper Seabold wrote:
On Mon, Feb 25, 2013 at 10:43 AM, Till Stensitzki mail.t...@gmx.de
wrote:
First, sorry that i didnt search for an old thread, but because i
disagree with
conclusion i would at least address my reason:
I don't like
On Mon, 2013-02-25 at 16:33 +, Nathaniel Smith wrote:
On Mon, Feb 25, 2013 at 3:10 PM, Sebastian Berg
sebast...@sipsolutions.net wrote:
Hello all,
currently the `__contains__` method or the `in` operator on arrays, does
not return what the user would expect when in the operation
On Fri, 2013-03-01 at 08:30 +0100, Nicolas Rougier wrote:
Hi,
I'm trying to increment an array using indexing and a second array for
increment values (since it might be a little tedious to explain, see below
for a short example).
Using direct indexing, the values in the example are
Hi,
there has been a request on the issue tracker for a step parameter to
linspace. This is of course tricky with the imprecision of floating
point numbers.
As a trade off, I was thinking of a step parameter that is used to
calculate the integer number of steps. However to be certain that it
On Fri, 2013-03-01 at 12:33 +, Henry Gomersall wrote:
On Fri, 2013-03-01 at 13:25 +0100, Sebastian Berg wrote:
there has been a request on the issue tracker for a step parameter to
linspace. This is of course tricky with the imprecision of floating
point numbers.
How
On Fri, 2013-03-01 at 13:34 +, Nathaniel Smith wrote:
On Fri, Mar 1, 2013 at 12:33 PM, Henry Gomersall h...@cantab.net wrote:
On Fri, 2013-03-01 at 13:25 +0100, Sebastian Berg wrote:
there has been a request on the issue tracker for a step parameter to
linspace. This is of course tricky
On Fri, 2013-03-01 at 15:07 +, Henry Gomersall wrote:
On Fri, 2013-03-01 at 10:01 -0500, Alan G Isaac wrote:
On 3/1/2013 9:32 AM, Henry Gomersall wrote:
there should be an equivalent for floats that
unambiguously returns a range for the half open interval
If I've understood
On Fri, 2013-03-01 at 10:49 -0500, Alan G Isaac wrote:
One motivation of this thread was that
adding a step parameter to linspace might make
things easier for beginners.
I claim this thread has put the lie to that,
starting with the initial post. So what is the
persuasive case for the
On Wed, 2013-03-06 at 12:42 -0600, Kurt Smith wrote:
On Wed, Mar 6, 2013 at 12:12 PM, Kurt Smith kwmsm...@gmail.com wrote:
On Wed, Mar 6, 2013 at 4:29 AM, Francesc Alted franc...@continuum.io
wrote:
I would not run too much. The example above takes 9 bytes to host the
structure, while
Hey,
how would I go about making a compile time flag for numpy to use as a
macro?
The reason is: https://github.com/numpy/numpy/pull/2735
so that it would be possible to compile numpy differently for debugging
if software depending on numpy is broken by this change.
Regards,
Sebastian
On Sat, 2013-03-09 at 17:17 +0100, Sebastian Berg wrote:
Hey,
how would I go about making a compile time flag for numpy to use as a
macro?
To be clear I mean an environment variable.
The reason is: https://github.com/numpy/numpy/pull/2735
so that it would be possible to compile numpy
On Thu, 2013-03-21 at 22:20 +0100, Ralf Gommers wrote:
Hi all,
It is the time of the year for Google Summer of Code applications. If
we want to participate with Numpy and/or Scipy, we need two things:
enough mentors and ideas for projects. If we get those, we'll apply
under the PSF
On Fri, 2013-03-29 at 19:08 -0700, Matthew Brett wrote:
Hi,
We were teaching today, and found ourselves getting very confused
about ravel and shape in numpy.
Summary
--
There are two separate ideas needed to understand ordering in ravel and
reshape:
Idea 1): ravel /
On Sat, 2013-03-30 at 12:45 -0700, Matthew Brett wrote:
Hi,
On Sat, Mar 30, 2013 at 11:55 AM, Sebastian Berg
sebast...@sipsolutions.net wrote:
On Fri, 2013-03-29 at 19:08 -0700, Matthew Brett wrote:
Hi,
We were teaching today, and found ourselves getting very confused
about ravel
On Sun, 2013-03-31 at 14:04 -0700, Matthew Brett wrote:
Hi,
On Sun, Mar 31, 2013 at 1:43 PM, josef.p...@gmail.com wrote:
On Sun, Mar 31, 2013 at 3:54 PM, Matthew Brett matthew.br...@gmail.com
wrote:
Hi,
On Sat, Mar 30, 2013 at 10:38 PM, josef.p...@gmail.com wrote:
On Sun, Mar
On Thu, 2013-04-04 at 12:40 -0700, Matthew Brett wrote:
Hi,
snip
So - to restate in other words - this :
np.reshape(a, (3, 4), order='F')
could reasonably mean one of two orthogonal things
1) Retrieve data from the array using first-to-last indexing, return
any memory layout you
On Thu, 2013-04-04 at 16:56 +0300, Jaakko Luttinen wrote:
I don't quite understand how einsum handles broadcasting. I get the
following error, but I don't understand why:
In [8]: import numpy as np
In [9]: A = np.arange(12).reshape((4,3))
In [10]: B = np.arange(6).reshape((3,2))
In [11]:
On Wed, 2013-04-10 at 11:45 +0200, Sebastian Berg wrote:
On Wed, 2013-04-10 at 11:54 +0300, Dmitrey wrote:
On 04/10/2013 10:31 AM, Robert Kern wrote:
snip
This is all good and nice, but Robert is still right. For dictionaries
to work predictable you need to ensure two things.
First
On Wed, 2013-04-10 at 11:45 +0200, Sebastian Berg wrote:
On Wed, 2013-04-10 at 11:54 +0300, Dmitrey wrote:
On 04/10/2013 10:31 AM, Robert Kern wrote:
You think comparing tracked bug counts across different projects
means anything? That's adorable. I admire your diligence at
addressing
On Wed, 2013-03-06 at 11:43 -0700, Charles R Harris wrote:
Hi All,
snip
The development branch has been accumulating stuff since last summer,
I suggest we look to get it out in May, branching at the end of this
month.
Hey,
maybe it is a bit early, but I was wondering. What are the things
On Fri, 2013-04-12 at 10:50 -0400, Andrew Nelson wrote:
I have written a differential evolution optimiser that i use for
curvefitting. As a genetic optimisation technique it is stochastic and
relies heavily on random number generators to do the minimisation. As
part
of the
Hey all,
just revisiting non-integer (index) deprecations (basically
https://github.com/numpy/numpy/pull/2891). I believe for all natural
integer arguments, it is correct to do a deprecation if the input is not
an integer. (Technically most of these go through PyArray_PyIntAsIntp,
and if not
Hey,
the MapIter API has only been made public in master right? So it is no
problem at all to change at least the mapiter struct, right?
I got annoyed at all those special cases that make things difficult to
get an idea where to put i.e. to fix the boolean array-like stuff. So
actually started
On Mon, 2013-04-15 at 11:16 -0600, Charles R Harris wrote:
On Mon, Apr 15, 2013 at 10:29 AM, Sebastian Berg
sebast...@sipsolutions.net wrote:
Hey,
the MapIter API has only been made public in master right? So
it is no
problem at all to change
On Mon, 2013-04-15 at 13:36 -0600, Charles R Harris wrote:
On Mon, Apr 15, 2013 at 1:27 PM, Sebastian Berg
sebast...@sipsolutions.net wrote:
On Mon, 2013-04-15 at 11:16 -0600, Charles R Harris wrote:
On Mon, Apr 15, 2013 at 10:29 AM, Sebastian Berg
On Wed, 2013-04-17 at 09:07 -0700, Chris Barker - NOAA Federal wrote:
On Wed, Apr 17, 2013 at 9:04 AM, Chris Barker - NOAA Federal
chris.bar...@noaa.gov wrote:
On Tue, Apr 16, 2013 at 8:23 PM, Zachary Ploskey zplos...@gmail.com wrote:
I'd say we need some more unit-tests!
speaking of
Hey,
so I ignored trying to redo MapIter (likely it is lobotomized at this
time though). But actually got a working new index parsing (still needs
cleanup, etc.). Also some of the fast paths are not yet put back. For
most pure integer indices it got a bit slower, if it actually gets too
much one
On Fri, 2013-04-19 at 08:03 -0700, Chris Barker - NOAA Federal wrote:
On Apr 18, 2013, at 11:33 PM, Nathaniel Smith n...@pobox.com wrote:
On 18 Apr 2013 01:29, Chris Barker - NOAA Federal
chris.bar...@noaa.gov wrote:
This has been annoying, particular as rank-zero scalars are kind
On Fri, 2013-04-19 at 23:02 +0530, Robert Kern wrote:
On Fri, Apr 19, 2013 at 9:40 PM, Sebastian Berg
sebast...@sipsolutions.net wrote:
Fun fact, array[()] will convert a 0-d array to a scalar, but do nothing
(or currently create a view) for other arrays. Which is actually a good
Hi,
just something that has been spooking around in my mind. Considering
that matrix indexing does not really support fancy indexing, I was
wondering about introducing a KeepDims flag. Maybe it is not worth it,
at least not unless other subclasses could make use of it, too. And a
big reason for
that you don't remove the part that we use for the
next 1.8 release.
thanks
Frédéric
On Tue, Apr 16, 2013 at 9:54 AM, Nathaniel Smith n...@pobox.com
wrote:
On Mon, Apr 15, 2013 at 5:29 PM, Sebastian Berg
sebast...@sipsolutions.net wrote:
Hey
moved to enhancing the Numpy version with
Pull Request 2970 [3]. With some input from Sebastian Berg the
percentile function was rewritten with further vectorization, but
neither of us felt fully comfortable with the final product. Can
someone look at implementation in the PR and suggest
On Tue, 2013-04-23 at 23:33 -0400, josef.p...@gmail.com wrote:
On Tue, Apr 23, 2013 at 6:16 PM, Sebastian Berg
sebast...@sipsolutions.net wrote:
On Tue, 2013-04-23 at 12:13 -0500, Jonathan Helmus wrote:
Back in December it was pointed out on the scipy-user list[1] that
numpy has
On Thu, 2013-04-25 at 09:16 -0600, Charles R Harris wrote:
Hi All,
I think it is time to start the runup to the 1.8 release. I don't know
of any outstanding blockers but if anyone has a PR/issue that they
feel needs to be in the next Numpy release now is the time to make it
known.
Sounds
On Thu, 2013-04-25 at 14:04 -0600, Charles R Harris wrote:
On Thu, Apr 25, 2013 at 1:51 PM, josef.p...@gmail.com wrote:
On Thu, Apr 25, 2013 at 3:40 PM, Robert Kern
robert.k...@gmail.com wrote:
On Thu, Apr 25, 2013 at 8:21 PM, Andrew Giessel
On Mon, 2013-04-29 at 11:15 -0400, josef.p...@gmail.com wrote:
Is there a available function to convert an int to binary
representation as sequence of 0 and 1?
Maybe unpackbits/packbits? It only supports the uint8 type, but you can
view anything as that (being aware of endianess where
On Tue, 2013-04-30 at 22:20 -0700, Matthew Brett wrote:
Hi,
On Tue, Apr 30, 2013 at 9:16 PM, Matthew Brett matthew.br...@gmail.com
wrote:
Hi,
On Tue, Apr 30, 2013 at 8:08 PM, Yaroslav Halchenko
li...@onerussian.com wrote:
could anyone on 32bit system with fresh numpy (1.7.1) test
On Wed, 2013-05-01 at 15:29 -0400, Yaroslav Halchenko wrote:
just for completeness... I haven't yet double checked if I have done it
correctly but here is the bisected commit:
aed9925a9d5fe9a407d0ca2c65cb577116c4d0f1 is the first bad commit
commit aed9925a9d5fe9a407d0ca2c65cb577116c4d0f1
On Wed, 2013-05-01 at 16:37 -0400, Yaroslav Halchenko wrote:
On Wed, 01 May 2013, Sebastian Berg wrote:
There really is no point discussing here, this has to do with numpy
doing iteration order optimization, and you actually *want* this. Lets
for a second assume that the old behavior
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